public void Learn(int batchcount)
{
foreach (var layer in Layers)
{
layer.Refresh();
}
for (int b = 0; b < batchcount; b++)
{
var buf = LearningReader.GetBuffer();
//var r = new Random();
//double segvl = 0;
//for (int c = 0; c < buf.Input.Channels; c++)
// for (int i = 0; i < buf.Input.Width; i++)
// for (int j = 0; j < buf.Input.Height; j++)
// {
// buf.Input.Buffer[c][i, j] = segvl;
// }
//buf.Input.Buffer[0][r.Next(0, buf.Input.Width / 2), r.Next(0, buf.Input.Height / 2)] = 1 - segvl;
//buf.Input.Buffer[1][r.Next(0, buf.Input.Width), 0] = 1 - segvl;
//buf.Input.Buffer[2][0, r.Next(0, buf.Input.Height)] = 1 - segvl;
//double segvh = 0.5;
//for (int c = 0; c < buf.Teacher.Channels; c++)
// for (int i = 0; i < buf.Teacher.Width; i++)
// for (int j = 0; j < buf.Teacher.Height; j++)
// {
// buf.Teacher.Buffer[c][i, j] = segvh;
// }
//for (int i = 0; i < 10; i++)
//{
// for (int j = 0; j < 10; j++)
// {
// buf.Teacher.Buffer[2][3 + i, 3 - 1 + j] = 1 - segvh;
// buf.Teacher.Buffer[2][3 + i, 3 + 1 + j] = 1 - segvh;
// buf.Teacher.Buffer[1][0 + i, 0 + j] = 1 - segvh;
// buf.Teacher.Buffer[0][3 - 1 + i, 3 + j] = 1 - segvh;
// }
//}
InferenceProcess(buf.Input);
LearnProcess(buf.Teacher);
Generation++;
Epoch = buf.Epoch;
Teacher = buf.Teacher;
}
Batch++;
Update();
}
public void Confirm(OpenCvSharp.Size sourceSize)
{
Layers[0].property.SetInputSize(sourceSize.Width, sourceSize.Height, LearningReader.ReadChannels);
for (int i = 1; i < Layers.Count; i++)
{
Layers[i].property.SetInputSize(
Layers[i - 1].property.Output.Width,
Layers[i - 1].property.Output.Height,
Layers[i - 1].property.Output.Channels);
}
for (int i = 0; i < Layers.Count - 1; i++)
{
Layers[i + 1].property.Input = Layers[i].property.Output;
Layers[i].property.Sigma = Layers[i + 1].property.Propagater;
}
if (LearningReader != null)
{
LearningReader.ModelReflection(GPU, new Common.ModelEdgeParameter()
{
InputSize = new OpenCvSharp.Size(Layers[0].property.Input.Width, Layers[0].property.Input.Height),
InputChannels = Layers[0].property.Input.Channels,
OutputSize = new OpenCvSharp.Size(Layers[Layers.Count - 1].property.Output.Width, Layers[Layers.Count - 1].property.Output.Height),
OutputChannels = Layers[Layers.Count - 1].property.Output.Channels,
});
LearningReader.Start();
}
if (InferenceReader != null)
{
InferenceReader.ModelReflection(GPU, new Common.ModelEdgeParameter()
{
InputSize = new OpenCvSharp.Size(Layers[0].property.Input.Width, Layers[0].property.Input.Height),
InputChannels = Layers[0].property.Input.Channels,
OutputSize = new OpenCvSharp.Size(Layers[Layers.Count - 1].property.Output.Width, Layers[Layers.Count - 1].property.Output.Height),
OutputChannels = Layers[Layers.Count - 1].property.Output.Channels,
});
InferenceReader.Start();
}
}
